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Minor update to HierarchicalNetwork documentation #83

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Merged
merged 2 commits into from
Jul 14, 2023
Merged

Minor update to HierarchicalNetwork documentation #83

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bae89e4
Update HierarchicalNetwork documentation
elseml Jul 11, 2023
57d95a1
Merge remote-tracking branch 'upstream/Development' into Development
elseml Jul 14, 2023
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5 changes: 3 additions & 2 deletions bayesflow/summary_networks.py
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Expand Up @@ -550,7 +550,8 @@ def __init__(self, networks_list, **kwargs):
that are aligned with the probabilistic structure of the processed data.

Note: The networks will start processing from the lowest hierarchical level (e.g., observational level)
up to the highest hierarchical level.
up to the highest hierarchical level. It is recommended to provide higher-level networks with more
expressive power to allow for an adequate compression of lower-level data.

Example: For two-level hierarchical models with the assumption of temporal dependencies on the lowest
hierarchical level (e.g., observational level) and exchangeable units at the higher level
Expand All @@ -574,7 +575,7 @@ def call(self, x, return_all=False, **kwargs):
----------
data : tf.Tensor of shape (batch_size, ..., data_dim)
Example, hierarchical data sets with two levels:
(batch_size, D, L, x_dim) -> reduces to
(batch_size, D, L, x_dim) -> reduces to (batch_size, out_dim).
return_all : boolean, optional, default: False
Whether to return all intermediate outputs (True) or just
the final one (False).
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